u/_KryptonytE_

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GHCopilot multipliers for paid plans

Quote: Each model has a premium request multiplier, based on its complexity and resource usage. If you are on a paid Copilot plan, your premium request allowance is deducted according to this multiplier.

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Cost of building and deploying AI models in Agent Platform

Quote: Gemini 3.5 Flash delivers near-Pro intelligence and parallel agentic execution at standard Flash-tier speed and cost.

Rant: I want to talk about the GHCopilot model multipliers and what this means for subscribers regardless of plan/tier. The above is a little context so the tech bros do not hallucinate and start AI slop posting comments based on assumptions and misinformation.

This is just the latest model example for illustrating the complexity and tradeoffs of choosing a provider. Looking at the recent trends of model multipliers made me think beyond the reasoning and explanation given to justify the said multipliers.

I just simply could not digest the numbers slapped on the newer models and the bigger picture of why and how such things get passed on to end users is beyond me. Does someone wake up and decide to hold a board meeting to then decide the random multiplier based on the name of the model or do they think the end users are just naive and not understand the optics of cost of inference vs value?

I'm just curious, how many of you think this is the right thing to do? I mean if this is the future, I might as well just start charging my clients with the same multipliers, mimic the reasoning quotes and have them stop worrying about why and how.

Would this work? It's a great business model, I need a favour from all the other devs to do the same to their clients too. This way, they do not have anywhere else left to go except pay for what we offer at our own pricing if they choose to have us use AI for faster shipping over traditional coding. After all, AI is for everyone, right? Cheers! 🥂

Using gpt 5.5 xhigh on opencode with GitHub connected as provider and its screeching slow to complete a task I am too lazy to do myself. For context, I prompted it to harden a compression for specified pass in video downscaling with video_compress. Finally had to stop it and get it done with Gemini 3.1 instead. It worked for 35 mins before I had to stop it because I knew it doesn't take this long and the other model did it in 9 mins with post edit tests.

Anyone else seeing the same behaviour? I'm only asking because I plan to use gpt 5.5 xhigh to run down my tokens by eom and if it's broke I might as well stick to Opus 4.7 for complex but precise tasks.

For anyone who still thinks there's hope, look at the trend and get prepared for what's coming. This week I've taken it upon myself to work on my personal projects and was able to get 60% of the actual code done by hand, old school, with headphones plugged in and felt good for the amount of time I spent instead of winging it with an agent.

Why's that you ask? It's because I refuse to pay, not because I can't - I just won't. Until I can get a good enough coding agent running reliably locally, I'll do what I do best - just work harder - I'll leave the smart work for later when tech bros have simmered down.

I’ve been a long-term power user of GitHub, VS Code Insiders, and Copilot, orchestrating workflows with them for both my day job and my personal projects. I wanted to open up a discussion about the ground realities many of us are facing with the recent ecosystem changes - basically, the elephant in the room.

Here is what it boils down to:-

The Enterprise Utopia: In a work setup where the business manages and foots the bill, the experience is beautifully frictionless. You fire up VS Code and Copilot, and it just works. No token anxiety, no rate-limit drama, no strings attached.

The Personal Penalty: Switch over to a personal setup, and the dynamic drastically shifts. Suddenly, we’re forced to micromanage token usage every time we launch VS Code or the GitHub CLI. (Yes, basic auto complete is free for now, but that’s entirely beside the point when you're utilizing heavy agentic coding).

My main gripe is how tightly knit and restrictive this ecosystem has become. We technically have everything we ever wished for at our fingertips, but we can't use it to its full potential. We are forced to choose between making do with substandard, heavily nerfed context limits enforced by the platform, or compromising on security/privacy by resorting to BYOK (like using cheaper Chinese models) just to bypass those artificial barriers.

This brings me to a few questions I think we all need to be asking:-

1. Why stay for the bloat? Why continue using a bloated, nerfed VS Code/Copilot setup when there are alternative, slimmer IDEs out there (like OpenCode, for instance) that offer direct access without a middleman nerfing your context window?

2. What is the actual lock-in? Apart from GitHub’s core utility storing, tracking, and sharing projects, what features are actually keeping end-users here that are genuinely on par with or better than the rising competition?

3. Is a mass migration imminent? With these pricing and policy changes, what is stopping power users and bootstrapped businesses from migrating? It makes far more sense to move toward compartmentalized, usage-based solutions for agentic workflows and hosting that are actually cutting-edge and lack these artificial limitations.

4. The cutover is trivial. Over the past year, most of us have already been parallel-testing various model providers, IDEs, and platforms. We know enough by now to realize that migrating is actually quite easy.

The question isn't 'how' to move anymore; it's simply 'why stay?' and 'when to jump?'.

Are we just going to stay flexible and adapt to these restrictive changes, hoping big tech suddenly pivots? Or is it time to take control of our stacks? We are end-users; we don't have insight into the internal deals and market analysis of big tech, which honestly makes our choice even easier. We just need to go where the friction is lowest and the context is uncapped.

Would love to hear your thoughts on this. Are you feeling the squeeze on personal projects too?

I know we can be rude and care less for others who can't afford expensive tokens but sometimes people can be literally stuck and might be depending on such things for their income.

Sharing is caring - afterall we did enjoy using GitHub while it was request based.

Hi fellow devs, I've been trying for months to build an actual hawkeye (ball detection and tracking/prediction model) that works on mobile platform. I initially tried with YOLO inference and on device inference but the model was never able to detect or track.predict when testing the model even with repeated training. I then moved to cloud compute thinking the mobile device inference was nerfed due to hardware constraints but still got the same results (no detection/tracking/prediction). Has anyone done something similar to Hawkeye or know somebody or some place I can visit or ask/learn about how to accomplish this? I tried a lot of AI but seems like they confidently built models that simply did not work practically.

Please help, I would appreciate any ideas, path or sources I can read and understand what is going wrong. I know this is possible because apps like fulltrack[dot]ai do this but I'm not able to find any opensource project or training models to compare the code against to find out what is wrong with my prediction model. Thank you.

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Sorry Mr.Agent you're not getting a break until the counter resets. I'm not touching my codebase until tomorrow - no reviews, no gates. I held back my prompt engineering skills just to not pile up my own QA and diff analysis backlogs but today we make an exception!
Who else is ripping these providers a new one EOM?

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As a solo dev and technology architect for DAP clients, I am grateful to the devs that made the tools that have helped me achieve and I'm sticking to my choices regardless of the companies making pricing/policy changes. I thought I will share a few things that might give the ones feeling doubtful to start new or in a dilemma to continue pushing to ship their dreams.

It's not easy to do things end to end on your own, there's a lot of choices involved initially and along the way but AI has helped me make the right ones by filling the knowledge gaps and answering what hides behind the unknown things that I haven't tried. This will not change and it shouldn't because I know I cannot learn everything and keep on top of my game without the assist.

I anticipated changes months ago by reading the room per say - silent rumours and watching other providers making changes long before Microsoft decided to. It's no surprise that tomorrow is coming - the only question is how we are working to minimize the workflow damage.

I provided suggestions and feedback - asked for help and recieved advice from fellow devs on subs, gave other providers a try to see what the fuss is about and which provider/pricing suits my requirements including some weird from both OpenAI and Google. Kept coming back to or never getting enough incentives to modify or add overhead to my existing setup much - OpenCode, Copilot agentic models work flawlessly with my cloud resources for the projects while keeping everything tidy and always ready for the next issue/feat/enhancement. This was an uphill task for one person to do for the entire project especially with complex requirements and features.

The bottom line is, I'm a professional and my clients believe and depend on me - there is no compromising this. With the changes with pricing and rate limiting - we can adapt to both and if you have a sane setup like mine, you might have half-solved them already way before these announcements were out.

Billing my clients for copilot usage higher than earlier seems fair enough and adding tools to my dev env to reduce token consumption while keeping the harness as vanilla as possible with local script/hook based automations for whatever the agents do. These are two things that solve real problems instead of hopping over in search of better solutions. Remember, the grass seems greener on the other side of the mountain. Don't get me wrong I do not code 50% by hand, maybe not even 25% of my code is diff reviewed line by line. I too adopted agentic coding and got addicted just like all the others but I do draft comprehensive plans 90% on my own and do not prompt agents without a plan first. This makes a huge difference and gives you so much control and steer the agents in the right path before they even start to read the code or make any changes to the codebase.

I know people are feeling cheated or hopeless but I hope this helps those who haven't got the basics yet to start now, you will not know everything at first but learn - explore, test and find out what matches your workflow and techstack. Everyone is unique and it's just a matter of time before you find the right setup for yourself and make the right decisions - with the agents working for you, take all the time you need without assuming things.

Cheers!!! 🥂